Nanometric Scale Surface science and the Markov chain Monte Carlo simulation of disordered systems

TL;DR

This paper explores the application of Markov chain Monte Carlo methods to surface science at nanometric scales, highlighting its potential for studying phase transitions and disordered systems with results aligning well with experiments.

Contribution

It introduces the use of MCMC techniques for nanometric surface systems and surveys models of disordered systems, filling a gap in phase transition studies at this scale.

Findings

Simulations agree with experimental data

MCMC effectively models disordered nanosystems

Highlights need for further research in surface phase transitions

Abstract

The Markov chain Monte Carlo method as a statistical mechanics technique for the study of macroscopic systems has furnished the scientific community with great knowledge and advances in the theory of phase transitions. While a number of Monte Carlo models have been proposed for the study of surface growth, these models have not nearly being studied as exhaustively as in the models of magnetic systems, a paradigm of which is the classical model of Ernest Ising. In particular, studies of phase transitions in surface/interface science at nanometric scales are almost non-existent. This article has been written to motivate research in this area of statistical mechanics from the perspective of surface science. In this article we survey the rudiments of the method along with some models of disordered systems such as magnetic systems, material fracture, nano-pattern formation under ion bombardment, and molecular chirality. We performed simulations of these models using the method and obtained results that are in excellent agreement with experimental observations.